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milleniums/High-Resolution-Remote-Sensing-Semantic-Segmentation-PyTorch

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High-Resolution-Remote-Sensing-Semantic-Segmentation-PyTorch

遥感也许还不能预测未来,但它一定会告诉你过去和现在,以及一步步见证着未来。

Update soon:

  • 膨胀预测
  • 后处理
  • 半监督方法:伪标签
  • 加入tensorboardX可视化输出

TODO:

  • 总结训练步骤、技巧
  • 分享预训练模型

教研室项目预测图展示

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使用TensorBoard查看各项指标以及可视化(img, GT, Pre)

  • 本地:
tensorboard --logdir=<your_log_dir>
  • 服务器:
#首先使用ssh登陆服务器并转发端口:
ssh -L 6006:127.0.0.1:6006 远程服务器用户名@远程服务器Ip
(ssh -L 本地端口:本地IP:远程端口 远程服务器用户名@远程服务器Ip)
#在服务器上运行tensorboard:
tensorboard --logdir=<your_log_dir>
#在浏览器里输入:
远程服务器Ip:6006
  • 各项指标样例

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  • 可视化测试集样例(img, GT, Pre)

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数据分享

Reference

https://github.com/kazuto1011/deeplab-pytorch
https://github.com/fregu856/deeplabv3
https://github.com/zijundeng/pytorch-semantic-segmentation
https://github.com/jwyang/dcn.pytorch
https://github.com/lin-honghui/tianchi_CountyAgriculturalBrain_top1?spm=5176.12282029.0.0.278c1bb8nTiHfq

Contact

author: hk
qq:3025531252
email: 3025531252@qq.com

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PyTorch实现高分遥感语义分割(地物分类)

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